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Skillsleann

leann

Data & analytics

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Updated 10-29 04:36

About this skill

LEANN operator

Instructions

  1. Identify the exact checkout and pin. From the jeo-skills repository root, run python3 .agent-skills/leann/scripts/preflight.py --repo /absolute/upstream --json (or invoke scripts/preflight.py from the installed skill root). An omitted --repo is inventory only. The helper compares selected pinned-file hashes; it does not prove Git HEAD, the whole checkout, installed dependencies, or runtime readiness. Read the pinned source notes.
  2. Keep the system model straight. LEANN is a vector index that uses graph-based selective recomputation to reduce stored embedding data. Its graph is an index/search optimization, not a semantic knowledge graph or durable code-architecture graph. Route the latter to mex or graphify.
  3. Plan local indexing before running it. Confirm source paths, file types/exclusions, index directory, chosen backend, embedding mode/model, and whether incremental updates or a full rebuild are intended. Check storage, memory, native dependencies, and data sensitivity.
  4. Get approval before effects. Ask before installing packages or downloading models; ingesting private, regulated, or third-party source material; calling paid or remote embedding APIs; starting a service or binding beyond loopback; creating/updating/rebuilding/deleting an index; or enabling integrations that read account/workspace data. Do not put keys in command history. A full rebuild (--force) is distinct from the default incremental build.
  5. Use the pinned CLI and verify the result. After approval, check the checkout's own leann --help and leann <command> --help; command options can change. Run a small representative index/search first, then verify expected source coverage and retrieval. Do not claim runtime readiness from preflight alone.

Examples

# Inspection only; use an absolute, non-symlink upstream checkout.
python3 .agent-skills/leann/scripts/preflight.py --repo /work/LEANN --json
Only after approval, in the inspected LEANN environment:

uv venv source .venv/bin/activate uv pip install leann leann build handbook --docs ./docs leann search handbook "how does the sync path work?" --top-k 5


## Best practices

- Treat indexing as data processing, not a harmless lookup. Review destination and any embedding endpoint before build.
- Prefer the default incremental path for a verified existing index; reserve `--force` for an approved rebuild with a recovery plan.
- Recheck backend/platform prerequisites against the pinned notes. LEANN's optional backends have different native/GPU requirements; do not infer support from the general Python package.
- Benchmark claims are workload-specific. Do not repeat upstream storage or retrieval percentages as guarantees for a user's corpus.
- Describe failures as offline-check failures, source-pin mismatches, dependency/setup failures, or runtime/retrieval failures; these are different states.

## References

- [Pinned upstream behavior, commands, limits, and source map](references/upstream.md)
- [Pin and source file hashes](references/source.json)
- [Authored routing and behavior scenarios](evals/evals.json)
- Helper contract: `python3 .agent-skills/leann/scripts/preflight.py --help`; helper supports Python 3.10+ on POSIX Linux/macOS/WSL2 and fails closed when secure directory traversal is unavailable, including unsupported native Windows.